US7697789B2 - System and method for enhancing stored binary images - Google Patents

System and method for enhancing stored binary images Download PDF

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Publication number
US7697789B2
US7697789B2 US11/413,203 US41320306A US7697789B2 US 7697789 B2 US7697789 B2 US 7697789B2 US 41320306 A US41320306 A US 41320306A US 7697789 B2 US7697789 B2 US 7697789B2
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Prior art keywords
image
image data
enhanced
continuous tone
adjustment
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US20070253631A1 (en
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Peter McCandlish
Ramesh Nagarajan
Clara Cuciurean-Zapan
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Xerox Corp
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Xerox Corp
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Assigned to XEROX CORPORTAION reassignment XEROX CORPORTAION ASSIGNMENT OF ASSIGNORS INTEREST (SEE DOCUMENT FOR DETAILS). Assignors: CUCIUREAN-ZAPAN, CLARA, MCCANDLISH, PETER, NAGARAJAN, RAMESH
Assigned to XEROX CORPORATION reassignment XEROX CORPORATION ASSIGNMENT OF ASSIGNORS INTEREST (SEE DOCUMENT FOR DETAILS). Assignors: CUCIUREAN-ZAPAN, CIARA, MCCANDLISH, PETER, NAGARAJAN,RAMESH
Priority to JP2007115513A priority patent/JP2007300624A/ja
Priority to EP07107224.3A priority patent/EP1850291B1/en
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    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
    • H04N1/00—Scanning, transmission or reproduction of documents or the like, e.g. facsimile transmission; Details thereof
    • H04N1/40—Picture signal circuits
    • H04N1/409—Edge or detail enhancement; Noise or error suppression
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
    • H04N1/00—Scanning, transmission or reproduction of documents or the like, e.g. facsimile transmission; Details thereof
    • H04N1/40—Picture signal circuits
    • H04N1/40075—Descreening, i.e. converting a halftone signal into a corresponding continuous-tone signal; Rescreening, i.e. combined descreening and halftoning

Definitions

  • the present disclosure relates to digital document production equipment and, more specifically, to the enhancement of binary images stored in digital document production equipment.
  • Digital document production equipment is very common in today's office environment.
  • such equipment which includes printers, copiers, facsimiles, and other multifunction (MF) machines, is configured to capture text and images as digital image data and either reproduce the captured text and images on media based on the digital image data or format the digital image data in a manner suitable for transport across a network.
  • MF multifunction
  • the digital signals are subsequently converted into binary image data.
  • the binary image data is then compressed and stored in memory and, upon printing, the stored compressed binary image data is read out of memory, decompressed, and forwarded to an output device, such as, for example, an image output terminal (IOT) to print the scanned image on a sheet.
  • IOT image output terminal
  • some MF machines include user-selectable image enhancement options that are applied to the continuous tone image prior to binarization.
  • Such continuous tone image formats are of higher resolution and typically comprise 8-bits (or higher) per pixel that represent greyscale or color images in the form of continuously varying tonal ranges.
  • the user-selected enhancement options adjust image features and artifacts by manipulating and/or transforming the continuous tone image data.
  • the enhanced continuous tone image data is then typically binarized and then supplied to the IOT. This results in an output image that has higher image quality and/or that has the user-selected image enhancement options applied to the input/scanned image.
  • More sophisticated MF machines offer a “store and retrieve” option, whereby stored image data may be later accessed and retrieved for future and different usage as originally intended.
  • the image data is stored in memory and may include the user-selected image enhancement options' information (i.e., image metadata).
  • image metadata the user-selected image enhancement options' information
  • the image data is stored in the compressed binary image data format—rather than the continuous tone image formats.
  • new image adjustments and enhancements effected by the user-selectable options cannot be applied.
  • binary image data is limited in its ability to accommodate image enhancements and improvements, the use of the “store and retrieve” feature becomes limited. For example it may force users to either re-copy the original image or settle for lower fidelity reproductions of the previously stored image.
  • a system and method of enhancing binary image data comprises retrieving the stored binary image data, converting the binary image data into higher-resolution image data, determining at least one image enhancement process, and applying the image enhancement process to the higher-resolution image data to produce an enhanced image.
  • the method further includes determining output format of the enhanced image and outputting the enhanced image.
  • the higher resolution image data may be of the continuous tone type.
  • the apparatus includes an image processing system module configured to perform image data conversions and enhancements, a memory module configured to store binary image data and metadata indicative of image attributes, an image output terminal module configured to output an image, a network interface module configured to enable communications with a network, and a controller
  • the controller module is configured to retrieve the stored binary image data from the memory module, initiate the conversion of the binary image data into higher-resolution image data by the image processing system, determine image enhancement processes, direct the image processing system to apply the image enhancement processes to the higher-resolution image data to produce an enhanced image, determine output format of the enhanced image, and output the enhanced image.
  • the image may be output to an image output terminal module in the form of a printer for printing the image. Also, the image may be transmitted to a network via a network interface module or sent to a remote fax destination through a fax interface module.
  • This embodiment may also, as an alternative, include the application of image enhancement processing, with the use of the metadata, to be performed in the background at times when the system is not busy and the storing of the subsequently processed image back into an Electronic Precollation Memory for sending of the additionally enhanced image to the IOT at a later time of the users choosing.
  • image enhancement processing with the use of the metadata, to be performed in the background at times when the system is not busy and the storing of the subsequently processed image back into an Electronic Precollation Memory for sending of the additionally enhanced image to the IOT at a later time of the users choosing.
  • FIG. 1 depicts a block diagram associated with the principal digital copying features of a MF machine
  • FIG. 2 depicts a system and method of applying image enhancement and image format manipulation options to binary image data.
  • FIG. 1 depicts a block diagram associated with the principal digital copying features of a MF machine 100 .
  • Such an apparatus is intended to cover scanners, printers, copiers, facsimiles, or other multifunction machines that are capable of reproducing images and documents.
  • the particular apparatus disclosed is merely an exemplary embodiment and, in no way, is it intended to be limiting.
  • MF machine 100 comprises controller module 102 , a user interface (UI) module 112 , a network interface (I/F) module 116 , an image input terminal (IIT) module 104 , an image processing system (IPS) module 106 , an electronic pre-collation system (EPC) module 108 with associated memory 110 , and an image output terminal (IOT) module 110 .
  • UI user interface
  • I/F network interface
  • IIT image input terminal
  • IPS image processing system
  • EPC electronic pre-collation system
  • IOT image output terminal
  • Controller module 102 is configured to manage and control the overall digital copier functionality of MF machine 100 as well coordinate communications and operations between the various modules. Controller 102 may, thus, comprise micro-processing circuitry, application-specific integrated circuitry (ASIC), or similar logic circuitry capable of processing information and instructions, responding to information requests, communicating with various associated modules, and executing commands. In so doing, controller 102 is configured to operate with executable instructions, such as software and/or firmware code, that effect the processes associated with the embodiments of the present invention.
  • executable instructions such as software and/or firmware code
  • IIT image input terminal
  • IPS image processing system
  • EPC electronic pre-collation system
  • IOT image output terminal
  • IIT 104 includes an image sensor that records reflected light from a series of small areas in the original image as the image moves past the sensor to yield a set of digital signals.
  • the digital signals are subsequently converted, by an image processing system (IPS) 106 , into binary image data.
  • the binary image data comprises lower resolution binary data formats. That is, for black and white images (such as black text on white background), the binary image data represents of the on/off state of white content in the image pixels and, therefore, has a 1-bit per pixel resolution. For color original images, the binary image data represents the on/off state of each of binary cyan, magenta, yellow, and black (CMYK) content of the image pixels.
  • the IPS 106 may use any known technique for processing the image, including applying transfer curves, linear and non linear filters, or color transformation matrices or tables to the image.
  • the IPS 106 then compresses the binary image data and stores the data in the memory 110 associated for example with electronic pre-collation system (EPC) 108 .
  • EPC electronic pre-collation system
  • EPC 108 is configured to store images and documents in electronic form and pre-collate the document pages.
  • the stored compressed binary image data is read out of EPC memory 110 , decompressed, and forwarded to image output terminal (IOT) 114 to print the scanned image on a sheet. That is, the IOT 114 prints the image onto a sheet of paper or other substrate medium.
  • IOT image output terminal
  • UI module 112 is configured to enable users to enter operation commands, or the like, and includes a user input section 112 A and display section 112 B.
  • the display section 112 B may comprise a liquid crystal display (LCD), for example, while user input section 112 A may comprise buttons.
  • both user input section 112 A and display section 112 B may comprise a touch panel.
  • user-selectable image enhancement options as well as store and retrieve options are communicated to controller module 102 via UI module 112 .
  • network interface (I/F) module 116 is configured to communicate and transport information to and from network 120 . That is, MF machine 100 may be coupled to network 120 for remotely accepting and performing printing tasks as well as being able to transport digital image data to a client across network 120 .
  • FIG. 2 depicts process 200 directed to effect image enhancements of stored, compressed, binary image data, in accordance with embodiments of the present invention.
  • a prior copy task has been initiated and that the “store and retrieve” option for future reproductions has been selected by the user, via UI module 112 , so that the original image has been scanned by IIT module 104 and the compressed binary image data has been stored in EPC memory 110 .
  • Image metadata may include attribute information, such as, copy settings, segmentation tag maps, as well as image processing parameters, such as prior image enhancement adjustment information.
  • Metadata may be included as part of the image data so that when it is converted to continuous tone there is extra information to undo/do certain processing for the retrieval.
  • one part of the metadata information could be Original Type mode (Photo, Text, Mixed) that the user had selected while scanning. This apriori information could be used to apply suitable look up table in the contone restoration process.
  • Metadata for user-selected settings may include original sub-type, background suppression, contrast enhancement, dynamic range adjustment, brightness adjustment, sharpness adjustment, hue adjustment, chrome adjustment, color balance, and saturation adjustment.
  • metadata could include data to direct further processing of the image (for example the background suppression) so that at a later time the user through the store and recall feature could select an image and the metadata would indicate that background suppression has been applied.
  • the binary image data is converted to continuous tone image data. That is for black and white images, the binary image data may be converted from the 1-bit per pixel data to an 8-bit per pixel greyscale image data, while for color images, the binary 4 planes of 1-bit per pixel CMYK image data may be converted to 32-bit (i.e., 8 bits per color plane) per pixel color image data.
  • Such a conversion may include methods such as the one using look up tables as described in U.S. Pat. No. 6,343,159, the entirety of which is incorporated herein by reference.
  • such a conversion may include methods such as the one using a digital filtering approach described in patent application Ser. No. 11/126,970, the entirety of which is incorporated herein by reference.
  • process 200 determines whether user-selectable image enhancement options have been selected, via UI 112 , for the retrieved image. If so, the user-selected image enhancement information is identified, in task 208 , and provided for processing to task 212 . If user-selectable image enhancement options have not been selected, automatic enhancement features are identified, in task 210 , and provided for processing to task 212 .
  • the automatic enhancement features may be based, for example, on the stored image metadata.
  • image enhancement may involve adjusting image features and artifacts by manipulating and/or transforming the continuous tone image data.
  • image enhancement may include, for example, original type, original subtype, background suppression, contrast enhancement, dynamic range adjustment, brightness adjustment, sharpness adjustment, hue adjustment, chroma adjustment, color balance adjustment, and saturation adjustment.
  • image enhancement may involve adaptive dynamic range adjustment via methods described in the patent application Ser. No. 11/275,078, which is incorporated herein by reference.
  • continuous tone image data is processed by applying the user-selected or automatically-provided image enhancement information.
  • this may include color space conversions. That is, 32-bit per pixel color image data, which resulted from the CMYK conversion in task 204 , may be transformed back to an improved version of the original color space (e.g., a device independent color space such as Lab or YCbCr color spaces).
  • the image metadata may include attribute information regarding the conversion of the original color space to continuous tone CMYK. This metadata may then be retrieved from EPC memory 110 and exploited to perform an as accurate as possible reverse transform to achieve the original color space.
  • the user-selected or automatically-provided image enhancement information may then be applied to the original color space, thereby rendering an enhanced, higher fidelity version of the image.
  • the enhanced original color space image may then be converted back to continuous tone 32 bit per pixel CMYK for processing or left in the original color space or converted to a 24 bit per pixel standard color space such as RGB.
  • process 200 determines, at task 214 , whether the enhanced image data is to be outputted as an enhanced continuous tone image or as an enhanced binary image. If the enhanced continuous tone image output is selected, then the enhanced continuous tone image is forwarded to an output device in the appropriate color space, in task 220 .
  • the output device may include IOT 114 , in which the enhanced continuous tone image is reproduced on a sheet.
  • the enhanced continuous tone image may be exported to a network 120 file system or e-mailed to a recipient or sent to remote fax destination through the fax interface module, thereby allowing the “store and retrieve” feature to operate as a “scan-to-file” task.
  • the enhanced continuous tone image is converted, in task 218 , as an enhanced binary image. That is, techniques, such as, error diffusion, dithering, and/or thresholding or any other type of halftoning are applied to the enhanced continuous tone image to generate the enhanced binary image.
  • This task also enables previously stored color images to be translated into black and white images.
  • the enhanced binary image is then forwarded to an output device, as described above, in task 220 .
  • controller module 102 may be modified with executable instructions and commands in conjunction with IPS module 106 , EPC module 108 , memory 110 , and/or UI 112 , to perform the above-identified process of enhancing stored binary images.

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  • Engineering & Computer Science (AREA)
  • Multimedia (AREA)
  • Signal Processing (AREA)
  • Image Processing (AREA)
  • Facsimile Image Signal Circuits (AREA)
  • Editing Of Facsimile Originals (AREA)
US11/413,203 2006-04-28 2006-04-28 System and method for enhancing stored binary images Expired - Fee Related US7697789B2 (en)

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JP2007115513A JP2007300624A (ja) 2006-04-28 2007-04-25 保存された２値画像データを増強する装置および方法
EP07107224.3A EP1850291B1 (en) 2006-04-28 2007-04-30 System and method for enhancing stored binary images

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Cited By (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20080013787A1 (en) * 2006-07-12 2008-01-17 Fujifilm Corporation Imaging apparatus, image processor, image filing method, image processing method and image processing program
US20090279145A1 (en) * 2005-12-23 2009-11-12 Xerox Corporation Image data processing system and method
US20110033131A1 (en) * 2006-08-08 2011-02-10 Xerox Corporation Methods for background and noise suppression in binary to grayscale image conversion
US20110181735A1 (en) * 2009-12-10 2011-07-28 Beyo Gmbh Method For Optimized Camera Position Finding For System With Optical Character Recognition

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* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US8130389B2 (en) * 2007-12-20 2012-03-06 Xerox Corporation Cost effective image path for multiple office applications
US8675957B2 (en) 2010-11-18 2014-03-18 Ebay, Inc. Image quality assessment to merchandise an item
US9721292B2 (en) 2012-12-21 2017-08-01 Ebay Inc. System and method for image quality scoring
KR20190011038A (ko) * 2017-07-24 2019-02-01 에이치피프린팅코리아 유한회사 화상형성장치, 이의 제어 방법 및 컴퓨터 판독가능 기록 매체
CN119647553A (zh) 2018-05-18 2025-03-18 谷歌有限责任公司 学习数据增强策略

Citations (9)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US4630125A (en) 1983-06-01 1986-12-16 Xerox Corporation Unscreening of stored digital halftone images
US5296909A (en) * 1990-09-07 1994-03-22 Alenia Aeritalia & Selenia S.P.A. Detector of suspended cables for avionic applications
US5506699A (en) 1993-04-27 1996-04-09 Wong; Ping W. Method and apparatus for converting a halftone image into a continuous tone image
US6021256A (en) * 1996-09-03 2000-02-01 Eastman Kodak Company Resolution enhancement system for digital images
US6289137B1 (en) * 1994-06-02 2001-09-11 Canon Kabushiki Kaisha Image processing apparatus and method
US6579324B1 (en) * 1999-04-30 2003-06-17 Microsoft Corporation Method for indicating a selected region on a computer display while allowing the user to see the formatting of the background and content items within the selected region
US6590676B1 (en) 1999-05-18 2003-07-08 Electronics For Imaging, Inc. Image reconstruction architecture
US6654062B1 (en) * 1997-11-13 2003-11-25 Casio Computer Co., Ltd. Electronic camera
US6690424B1 (en) * 1997-03-19 2004-02-10 Sony Corporation Exposure control apparatus for controlling the exposure of an image pickup plane in a camera

Family Cites Families (12)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
JPH04219073A (ja) * 1990-10-11 1992-08-10 Ricoh Co Ltd 画像記録装置
US5760922A (en) * 1993-10-08 1998-06-02 Matsushita Electric Industrial Co., Ltd. Area recognizing device and gradation level converting device employing area recognizing device
JP3380065B2 (ja) * 1993-10-08 2003-02-24 松下電器産業株式会社 領域識別装置及び階調変換処理装置
JP3380831B2 (ja) * 1996-03-08 2003-02-24 シャープ株式会社 画像形成装置
US5799112A (en) * 1996-08-30 1998-08-25 Xerox Corporation Method and apparatus for wavelet-based universal halftone image unscreening
JP3967336B2 (ja) * 1996-09-30 2007-08-29 株式会社リコー 色変換処理装置，色変換処理方法並びにその方法をコンピュータに実行させるプログラムを記録したコンピュータ読み取り可能な記録媒体
US6343159B1 (en) * 1998-12-23 2002-01-29 Xerox Corporation Method and apparatus for modeling and reconstruction of halftoned images
JP2003179749A (ja) * 2001-12-11 2003-06-27 Fujitsu Ltd データ変換方法
JP2004112140A (ja) * 2002-09-17 2004-04-08 Ricoh Co Ltd 画像処理装置
US7376268B2 (en) * 2002-09-17 2008-05-20 Ricoh Company, Limited Image processing apparatus for transmitting image data to an external device
US7105113B2 (en) * 2003-07-11 2006-09-12 Urethane International Llc Method for flatproofing a tire and wheel assembly and resulting flatproofed assembly
US20050063013A1 (en) * 2003-09-22 2005-03-24 Xerox Corporation Enhancing black & white image quality with limited image processing resources

Patent Citations (9)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US4630125A (en) 1983-06-01 1986-12-16 Xerox Corporation Unscreening of stored digital halftone images
US5296909A (en) * 1990-09-07 1994-03-22 Alenia Aeritalia & Selenia S.P.A. Detector of suspended cables for avionic applications
US5506699A (en) 1993-04-27 1996-04-09 Wong; Ping W. Method and apparatus for converting a halftone image into a continuous tone image
US6289137B1 (en) * 1994-06-02 2001-09-11 Canon Kabushiki Kaisha Image processing apparatus and method
US6021256A (en) * 1996-09-03 2000-02-01 Eastman Kodak Company Resolution enhancement system for digital images
US6690424B1 (en) * 1997-03-19 2004-02-10 Sony Corporation Exposure control apparatus for controlling the exposure of an image pickup plane in a camera
US6654062B1 (en) * 1997-11-13 2003-11-25 Casio Computer Co., Ltd. Electronic camera
US6579324B1 (en) * 1999-04-30 2003-06-17 Microsoft Corporation Method for indicating a selected region on a computer display while allowing the user to see the formatting of the background and content items within the selected region
US6590676B1 (en) 1999-05-18 2003-07-08 Electronics For Imaging, Inc. Image reconstruction architecture

Non-Patent Citations (4)

* Cited by examiner, † Cited by third party
Title
Fan, "Retrieval of Gray Images From Digital Halftones," IEEE, 1992, pp. 2477-2480.
Hein et al., "Reconstruction of Continuous Tone Images From Their Error-Diffused Halftone Version," SPIE, vol. 1913, 1993, pp. 310-324.
Kite et al., "A High Quality, Fast Inverse Halftoning Algorithm for Error Diffused Halftones," Proceedings of the IEEE International Conference on Image Processing, vol. 2, Oct. 4-7, 1998, pp. 59-63.
Miceli et al., "Inverse Halftoning," Journal of Electronic Imaging, vol. 1, No. 2, Apr. 1992, pp. 143-151.

Cited By (7)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20090279145A1 (en) * 2005-12-23 2009-11-12 Xerox Corporation Image data processing system and method
US8139873B2 (en) * 2005-12-23 2012-03-20 Xerox Corporation Binary image data processing system and method
US20080013787A1 (en) * 2006-07-12 2008-01-17 Fujifilm Corporation Imaging apparatus, image processor, image filing method, image processing method and image processing program
US20110033131A1 (en) * 2006-08-08 2011-02-10 Xerox Corporation Methods for background and noise suppression in binary to grayscale image conversion
US8041143B2 (en) 2006-08-08 2011-10-18 Xerox Corporation Methods for background and noise suppression in binary to grayscale image conversion
US20110181735A1 (en) * 2009-12-10 2011-07-28 Beyo Gmbh Method For Optimized Camera Position Finding For System With Optical Character Recognition
US8135217B2 (en) * 2009-12-10 2012-03-13 Beyo Gmbh Method for optimized camera position finding for system with optical character recognition

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EP1850291B1 (en) 2015-10-14
JP2007300624A (ja) 2007-11-15
EP1850291A2 (en) 2007-10-31

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